Triple

T932083
Position Surface form Disambiguated ID Type / Status
Subject A Mercy E20114 entity
Predicate hasCharacter P2308 FINISHED
Object Florens
Florens is a young enslaved girl and central narrator in Toni Morrison’s novel "A Mercy," whose perspective reveals the brutal realities of early colonial America.
 E109667 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Florens | Statement: [A Mercy, hasCharacter, Florens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Florens
Context triple: [A Mercy, hasCharacter, Florens]
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • C. Ludovica
    Ludovica is an Italian feminine given name, traditionally associated with nobility and derived from the same Germanic roots as names like Louise and Ludwig.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Vian
    Vian is a surname most notably associated with British Royal Navy Admiral Philip Vian, who served with distinction during both World Wars.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Florens
Triple: [A Mercy, hasCharacter, Florens]
Generated description
Florens is a young enslaved girl and central narrator in Toni Morrison’s novel "A Mercy," whose perspective reveals the brutal realities of early colonial America.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Florens
Target entity description: Florens is a young enslaved girl and central narrator in Toni Morrison’s novel "A Mercy," whose perspective reveals the brutal realities of early colonial America.
  • A. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • B. Franziska
    Franziska is a feminine given name of German origin, closely related to and cognate with the name Frances.
  • C. Ludovica
    Ludovica is an Italian feminine given name, traditionally associated with nobility and derived from the same Germanic roots as names like Louise and Ludwig.
  • D. Luisa
    Luisa is a feminine given name used in various languages, particularly Romance languages, as a form of the name Louise.
  • E. Vian
    Vian is a surname most notably associated with British Royal Navy Admiral Philip Vian, who served with distinction during both World Wars.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b34c457c819085cbfa0c798cb4c6 completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee1108188190a26c73864c697061 completed March 4, 2026, 8:32 a.m.
NEDg Description generation batch_69a7f1a1214481909538745d5713e402 completed March 4, 2026, 8:47 a.m.
NED2 Entity disambiguation (via description) batch_69a7f2303534819094ae764b20d223ee completed March 4, 2026, 8:49 a.m.
Created at: March 1, 2026, 7:40 p.m.